Physical Sciences and Mathematics Commons^™

Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud

BAU Journal - Science and Technology

With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Electrochemical Performance Of Porous Ceramic Supported Tubular Solid Oxide Electrolysis Cell, Heng-Ji Wang, Wen-Guo Chen, Zhou-Yi Quan, Kai Zhao, Yi-Fei Sun, Min Chen, Ogenko Volodymyr

Journal of Electrochemistry

Solid oxide electrolysis cell (SOEC) is an efficient and clean energy conversion technology that can utilize electricity obtained from renewable resources, such as solar, wind, and geothermal energy to electrolyze water and produce hydrogen. The conversion of abundant intermittent energy to hydrogen energy would facilitate the efficient utilization of energy resources. SOEC is an all-ceramic electrochemical cell that operates in the intermediate to high temperature range of 500–750 ℃. Compared with traditional low temperature electrolysis technology (e.g., alkaline or proton exchange membrane cells operating at ~100 ℃), the high-temperature SOEC can increase the electrolysis efficiency from 80% to ~100%, providing …

Nitrogen-Doped Graphite Felt On The Performance Of Aqueous Quinone-Based Redox Flow Batteries, Heng Zhang, Li-Xing Xia, Shan Jiang, Fu-Zhi Wang, Zhan-Ao Tan

Journal of Electrochemistry

Modification of electrode is vitally important for achieving high energy efficiency in aqueous quinone-based redox flow batteries (AQRFBs). The modification of graphite felt (GF) was carried out by means of urea hydrothermal reaction, and simultaneously, the effects of hydrothermal reaction time on the functional groups and surface structure of nitrogen-doped graphite felt were studied. The surface morphology and defect, element content and surface chemical state of the modified electrode were characterized by scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) test, Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The electrochemical performance of the modified electrodes was evaluated by cyclic voltammetry, electrochemical impedance …

An In-Situ Raman Spectroscopic Study On The Interfacial Process Of Carbonate-Based Electrolyte On Nanostructured Silver Electrode, Yu Gu, Yuan-Fei Hu, Wei-Wei Wang, En-Ming You, Shuai Tang, Jian-Jia Su, Jun Yi, Jia-Wei Yan, Zhong-Qun Tian, Bing-Wei Mao

Journal of Electrochemistry

The solid-electrolyte interphase (SEI) plays a key role in anodes for rechargeable lithium-based battery technologies. However, a thorough understanding in the mechanisms of SEI formation and evolution remains a major challenge, hindering the rapid development and wide applications of Li-based batteries. Here, we devise a borrowing surface-enhanced Raman scattering (SERS) activity strategy by utilizing a size optimized Ag nanosubstrate to in-situ monitor the formation and evolution of SEI, as well as its structure and chemistry in an ethylene carbonate-based electrolyte. To ensure a reliable in-situ SERS investigation, we designed a strict air-tight Raman cell with a three-electrode configuration. Based on …

A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …

Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol

Turkish Journal of Electrical Engineering and Computer Sciences

Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches' results not only …

Feature Selection Optimization With Filtering And Wrapper Methods: Two Disease Classification Cases, Serhat Ati̇k, Tuğba Dalyan

Turkish Journal of Electrical Engineering and Computer Sciences

Discarding the less informative and redundant features helps to reduce the time required to train a learning algorithm and the amount of storage required, improving the learning accuracy as well as the quality of results. In this study, we present different feature selection approaches to address the problem of disease classification based on the Parkinson and Cardiac Arrhythmia datasets. For this purpose, first we utilize three filtering algorithms including the Pearson correlation coefficient, Spearman correlation coefficient, and relief. Second, metaheuristic algorithms are compared to find the most informative subset of the features to obtain better classification accuracy. As a final …

New Modified Carrier-Based Level-Shifted Pwm Control For Npc Rectifiers Considered For Implementation In Ev Fast Chargers, Merve Mollahasanoğlu, Hakki Mollahasanoğlu, Hali̇l İbrahi̇m Okumuş

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the aim is to evaluate three-phase (3?) AC/DC neutral point-clamped (NPC) power factor corrected (PFC) multilevel converter performance for electric vehicle (EV) fast chargers. Power factor correction for EV fast chargers is very important in terms of efficient power usage and charger compatibility with the grid. Multilevel converters improve charging efficiency, reduce voltage stresses on components, minimize electromagnetic interference, and support high power capabilities. For this reason, multilevel converters with the PFC feature contribute to the reliable and effective operation of the fast-charging infrastructure. Rectifier analysis is tested with extensive simulations using a new modified carrier-based level-shifted …

A Comparative Study Of Yolo Models And A Transformer-Based Yolov5 Model For Mass Detection In Mammograms, Damla Coşkun, Dervi̇ş Karaboğa, Alper Baştürk, Bahri̇ye Akay, Özkan Ufuk Nalbantoğlu, Serap Doğan, İshak Paçal, Meryem Altin Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is a prevalent form of cancer across the globe, and if it is not diagnosed at an early stage it can be life-threatening. In order to aid in its diagnosis, detection, and classification, computer-aided detection (CAD) systems are employed. You Only Look Once (YOLO)-based CAD algorithms have become very popular owing to their highly accurate results for object detection tasks in recent years. Therefore, the most popular YOLO models are implemented to compare the performance in mass detection with various experiments on the INbreast dataset. In addition, a YOLO model with an integrated Swin Transformer in its backbone …

Machine Learning Based Bioinformatics Analysis Of Intron Usage Alterations And Metabolic Regulation In Adipose Browning, Hamza Umut Karakurt, Pinar Pi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Adipose tissue is the major energy depot of the body and is considered an endocrine organ. Adipose tissue involves many different cell types, first and foremost, the adipocytes. White adipose cells that store fat and brown adipocytes that take part in lipid oxidation and heat generation are the most common cell types in adipose tissue. Even though brown adipocytes which have a high number of mitochondria and high fat-burning capacity are rare in adults, they are abundant in newborns and rodents. White adipocytes can gain a temporal brown-like character with a process called browning, which can be induced with cold …

Charge Transfer Evaluation In Solid Insulating Materials Encapsulating The Gaseous Voids Of Submillimeter Dimensions Using Transmission Line Method, Amin Shamsi, Alireza Ganjovi, Amir Abas Shayegani Akmal

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, using a lumped RC circuit model which is based on transmission line modeling (TLM) method, the charge transfer in a solid insulating system encapsulating a gaseous void of submillimeter dimensions is evaluated. Here, both the dielectric material and gaseous void are considered simultaneously as a transmission line. The transmission line includes the capacitive and resistance elements and, the obtained circuit equations were coupled with the continuity and kinetic energy equations for charged species along with Poisson's equation. These equations are solved via 4th order Runge-Kutta method and, the electric field and potential, density of all the charged …

Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility …

Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Stance detection has garnered considerable attention from researchers due to its broad range of applications, including fact-checking and social computing. While state-of-the-art stance detection models are usually based on supervised machine learning methods, their effectiveness is heavily reliant on the quality of training data. This problem is more prevalent in stance detection task because the stance of a text is intimately tied to the target under consideration. While numerous datasets exist for stance detection, determining their suitability for a specific target can be challenging. In this work, we focus on Turkish stance detection and explore the impact of training data …

A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty

Turkish Journal of Electrical Engineering and Computer Sciences

Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …

A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe

Turkish Journal of Electrical Engineering and Computer Sciences

Blind source separation is a popular research topic used for decomposing mixed signals, particularly in the field of music. In addition to exploring machine learning-based approaches, this study aims to examine the performance of classical algorithms in separating audio signal sources. The evaluation of different genres is a significant aspect of this study as the performance of the methods may vary across various musical genres and different audio components. This consideration provides a novel perspective and contributes to a comprehensive analysis of the algorithms. Using the MusDB-HQ dataset, we conducted experimental studies comparing classical algorithms, including FastICA, NMF, and DUET, …

Constructing Carbon-Encapsulated Nifev-Based Electrocatalysts By Alkoxide-Based Self-Template Method For Oxygen Evolution Reaction, En-Hui Ma, Xu-Po Liu, Tao Shen, De-Li Wang

Journal of Electrochemistry

The development of green and sustainable water-splitting hydrogen production technology is beneficial to reducing the over-reliance on fossil fuels and realizing the strategic goal of "carbon neutral". As one of the half reactions for water splitting, oxygen evolution reaction has suffered the problems of sluggish four-electron transfer process and relatively slow reaction kinetics. Therefore, exploring efficient and stable catalysts for oxygen evolution reaction is of critical importance for water-splitting technology. Metal alkoxides are a series of compounds formed by the coordination function of metal ions with alcohol molecules. Metal alkoxides possess the double advantages of organic materials and inorganic materials, …

Peg-Water Electrolyte For High-Performance Zinc Iodine Dual-Ion Batteries, Xiao-Feng Qu, Yu-Ting Tang, Xin-Cheng He, Jia-Sheng Zhou, Zi-Heng Tang, Wen-Hua Feng, Jun Liu

Journal of Electrochemistry

Thanks to abundant resource and rapid redox reaction kinetics, iodine is regarded as promising positive materials inthe batteries. However, the shuttling effect due to the high solubility of iodine in the electrolyte makes the performance of battery poor. In this paper, polyethylene glycol (PEG400) and potassium iodide were added into zinc-ion aqueous electrolyte. PEG400 could complex with iodine to reduce the dissolution of iodine, therefore alleviating the formation of soluble triiodide (I₃^–) from iodine and iodide ions. Furthermore, this electrolyte was used in the battery with double carbon cloths as the current collectors, double separators and zinc …

Preparation And Lithium Storage Properties Of Carbon Confined Li3Vo4 Nano Materials, Jia-Qi Fan, Huan-Qiao Song, Jia-Ying An, Amantai A-Yi-Da-Na, Mo Chen

Journal of Electrochemistry

Li₃VO₄, as a promising anode material for lithium ion batteries, has been widely studied because of its low and safe voltage, and large capacity. However, its poor electronic conductivity impedes the practical application of Li₃VO₄ particularly at high rates. In this paper, carbon confined Li₃VO₄ nano materials (Li₃VO₄/C) were synthesized by hydrothermal and solid-phase method, and for comparison, the Li₃VO₄ (N) nano materials without carbon confinement and Li3VO4 (B) materials were also synthesized by pure solid-phase method. The composition, structure, morphology and specific …

Lif-Sn Composite Modification Layer To Modify Garnet/Lithium Metal Interface, Wu Yang, Xue-Fan Zheng, Yu-Qi Wu, Zheng-Liang Gong

Journal of Electrochemistry

The growing demands for electric vehicles and consumer electronics; as well as the expanding renewable energy storage market; have promoted extensive research on energy storage technologies with low costhigh energy density and safety. Lithium (Li) metal and solid-state electrolytes are considered as important components for next-generation batteries because of their great potential for improvements in energy density and safety performance. Inorganic garnet-type solid electrolytes with high Li-ion conductivity (about 10^-3 S·cm^-1) and high shear modulus (55 GPa) are considered to be ideal solid-state electrolytes; however; the issue of Li dendrite growth still obstructs their practical application. Herein; …

The Algorithm For The Design Of Fine Granular Substances’ Smart-Type Heat And Moisture Converters Based On Their Accuracy And Speed Criteria, Erkin Uljaev, Ali Abduakhatovich Abduraxmanov

Chemical Technology, Control and Management

The paper describes a technique and algorithm allowing to perform parametric design of smart-type heat and moisture converters (hereinafter SHMC) of fine-grained dispersive materials based on their criteria of accuracy and speed. The proposed algorithm optimizes the process of design of smart-type switches and ensure optimal performance of the switches. The method of calculation and selection of optimal parameters of smart-type heat and moisture converters intended to be used in the measurement of parameters such as heat and humidity of fine dispersive substances are aimed at boosting two parameters, i.e., the accuracy and speed. Also, the design stages have been …

Research Progress And Performance Improvement Strategies Of Hard Carbon Anode Materials For Sodium-Ion Batteries, Xiu-Ping Yin, Yu-Feng Zhao, Jiu-Jun Zhang

Journal of Electrochemistry

This paper systematically summarizes the research progress of hard carbon anode materials in sodium ion batteries(SIBs) and the development of the corresponding sodium storage mechanism in recent years, and reviews the performance improvement strategies of hard carbon materials from the aspects of structural design and electrolyte regulation. The effects of the selection of precursors, carbonization temperature, pretreatment, pore formers, heteroatom doping, material compounding, electrolyte regulation and pre-sodiumization on the sodium storage performance of hard carbon anode materials are briefly described. This paper provides new insights into the design, synthesis and electrolyte
matching of high-performance and low-cost hard carbon materials, and …

Preparation And Electrocatalytic Performance Of Feni-Cop/Nc Bifunctional Catalyst, Si-Miao Liu, Jing-Jiao Zhou, Shi-Jun Ji, Zhong-Sheng Wen

Journal of Electrochemistry

Rechargeable zinc-air batteries have gradually attracted much attention worldwide due to their high capacity, high energy density and low price. Oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) correspond to the charging and discharging processes in rechargeable zinc-air battery, respectively. At present, commercial Pt/C and IrO₂ catalysts hinder the large-scale application of zinc-air batteries due to low reserves, high prices and poor stability. Therefore, exploring high performance, low cost and high stability with dual functional catalysts is important for the development of rechargeable zinc-Air batteries. The metal-organic frameworks (MOFs) have high specific surface area, structural stability, good catalytic …

Surface Modifications Of Lini0.96Co0.02Mn0.02O2 With Tungsten Oxide And Phosphotungstic Acid, Gang Zhao, Zheng-Liang Gong, Yi-Xiao Li, Yong Yang

Journal of Electrochemistry

With the rapid development of electric vehicles, enormous demands are made for higher energy density, better cycling performance and lower cost of lithium-ion batteries (LIBs). As an important high capacity cathode material for LIBs, the high nickel layered oxide material LiNi_0.8Co_0.1Mn_0.1O₂(NCM811) can reach an energy density of 760 Wh·kg^-1. The ultra-high nickel ternary positive electrode material (LiNi_1-x-yCo_xMn_yO₂, x ≥ 0.90) has a specific capacity of more than 210 mAh·g^-1, and can realize higher energy density. Besides, an ultra-high nickel material …

Dynamic Mechanism Of Science Based Technological Innovation And Industrial Evolution—Take Semiconductor, Digital Computer And Radio Technologies As Examples, Yi Zhang, Qiang Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

By studying the technological innovation and industrial development process of semiconductor, digital computer and radio, this study analyzes the path, conditions and force of science-based technological innovation and its industrialization, establishes a chain reaction model of large-scale technological innovation and diffusion, and compares it with market-based technological innovation. It is found that the large-scale aggregation of scientific research institutions and industrial laboratories accelerates the speed of technological innovation, and diffuses along two paths of scientific research institutions to enterprises and enterprises to enterprises, forming a chain reaction of large-scale technological innovation. Strategic demand is the basic driving force for the …

Fortifying Iot Against Crimpling Cyber-Attacks: A Systematic Review, Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir

Karbala International Journal of Modern Science

The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infrastructure. However, alongside the immense benefits, the widespread adoption of IoT also brings a complex web of security threats that can influence society, policy, and infrastructure conditions. IoT devices are particularly vulnerable to security violations, and industrial routines face potentially damaging vulnerabilities. To ensure a trustworthy and robust security framework, it is crucial to …

Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi

Karbala International Journal of Modern Science

The rapid development of the Internet and network services coupled with the growth of communication infrastructure necessitates the employment of intelligent systems. The complexity of the network is heightened by these systems, as they offer diverse services contingent on traffic type, user needs, and security considerations. In this context, a service function chain offers a toolkit to facilitate the management of intricate network systems. However, various traffic types require dynamic adaptation in the sets of function chains. The problem of optimizing the order of service functions in the chain must be solved using the proposed approach, along with balancing the …

Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram

Turkish Journal of Electrical Engineering and Computer Sciences

Hyperspectral imaging has emerged as a prominent area of research in the field of remote sensing science. However, hyperspectral images (HSIs) pose a notable challenge due to the presence of numerous irrelevant and redundant spectral bands exhibiting high correlation. Therefore, it is necessary to enhance the classification performance for HSI processing by selecting the most relevant discriminative spectral bands. To this end, this paper introduces a metaheuristic search method called enhancing exploration-exploitation in harmony search (E3HS). The standard harmony search suffers from many weaknesses, such as premature convergence and falling easily into the local optimum. Consequently, E3HS was proposed to …

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi

Turkish Journal of Electrical Engineering and Computer Sciences

Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …

Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson

Turkish Journal of Electrical Engineering and Computer Sciences

Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …